Were the Victorians cleverer than us? The decline in general intelligence estimated from a meta-analysis of the slowing of simple reaction time

Is the Exposome Involved in Brain Disorders through the Serotoninergic System?

Serotonin (5-hydroxytryptamine, 5-HT) is a biogenic monoamine acting as a neurotransmitter in the central nervous system (CNS), local mediator in the gut, and vasoactive agent in the blood. It has been linked to a variety of CNS functions and is implicated in many CNS and psychiatric disorders. The high comorbidity between some neuropathies can be partially understood by the fact that these diseases share a common etiology involving the serotoninergic system. In addition to its well-known functions, serotonin has been shown to be a mitogenic factor for a wide range of normal and tumor cells, including glioma cells, in vitro. The developing CNS of fetus and newborn is particularly susceptible to the deleterious effects of neurotoxic substances in our environment, and perinatal exposure could result in the later development of diseases, a hypothesis known as the developmental origin of health and disease. Some of these substances affect the serotoninergic system and could therefore be the source of a silent pandemic of neurodevelopmental toxicity. This review presents the available data that are contributing to the appreciation of the effects of the exposome on the serotoninergic system and their potential link with brain pathologies (neurodevelopmental, neurodegenerative, neurobehavioral disorders, and glioblastoma).

Predicting Age From Behavioral Test Performance for Screening Early Onset of Cognitive Decline

Background: Neuronal reactions and cognitive processes slow down during aging. The onset, rate, and extent of changes vary considerably from individual to individual. Assessing the changes throughout the lifespan is a challenging task. No existing test covers all domains, and batteries of tests are administered. The best strategy is to study each functional domain separately by applying different behavioral tasks whereby the tests reflect the conceptual structure of cognition. Such an approach has limitations that are described in the article. Objective: Our aim was to improve the diagnosis of early cognitive decline. We estimated the onset of cognitive decline in a healthy population, using behavioral tests, and predicted the age group of an individual. The comparison between the predicted ("cognitive") and chronological age will contribute to the early diagnosis of accelerated aging. Materials and Methods: We used publicly available datasets (POBA, SSCT) and Pearson correlation coefficients to assess the relationship between age and tests results, Kruskal-Wallis test to compare distribution, clustering methods to find an onset of cognitive decline, feature selection to enhance performance of the clustering algorithms, and classification methods to predict an age group from cognitive tests results. Results: The major results of the psychophysiological tests followed a U-shape function across the lifespan, which reflected the known inverted function of white matter volume changes. Optimal values were observed in those aged over 35 years, with a period of stability and accelerated decline after 55-60 years of age. The shape of the age-related variance of the performance of major cognitive tests was linear, which followed the trend of lifespan gray matter volume changes starting from adolescence. There was no significant sex difference in lifelong dynamics of major tests estimates. The performance of the classification model for identifying subject age groups was high. Conclusions: ML models can be designed and utilized as computer-aided detectors of neurocognitive decline. Our study demonstrated great promise for the utility of classification models to predict age-related changes. These findings encourage further explorations combining several tests from the cognitive and psychophysiological test battery to derive the most reliable set of tests toward the development of a highly-accurate ML model.

Brain Disorders and Chemical Pollutants: A Gap Junction Link?

The incidence of brain pathologies has increased during last decades. Better diagnosis (autism spectrum disorders) and longer life expectancy (Parkinson's disease, Alzheimer's disease) partly explain this increase, while emerging data suggest pollutant exposures as a possible but still underestimated cause of major brain disorders. Taking into account that the brain parenchyma is rich in gap junctions and that most pollutants inhibit their function; brain disorders might be the consequence of gap-junctional alterations due to long-term exposures to pollutants. In this article, this hypothesis is addressed through three complementary aspects: (1) the gap-junctional organization and connexin expression in brain parenchyma and their function; (2) the effect of major pollutants (pesticides, bisphenol A, phthalates, heavy metals, airborne particles, etc.) on gap-junctional and connexin functions; (3) a description of the major brain disorders categorized as neurodevelopmental (autism spectrum disorders, attention deficit hyperactivity disorders, epilepsy), neurobehavioral (migraines, major depressive disorders), neurodegenerative (Parkinson's and Alzheimer's diseases) and cancers (glioma), in which both connexin dysfunction and pollutant involvement have been described. Based on these different aspects, the possible involvement of pollutant-inhibited gap junctions in brain disorders is discussed for prenatal and postnatal exposures.

Methodological Problems With Online Concussion Testing

Reaction time testing is widely used in online computerized concussion assessments, and most concussion studies utilizing the metric have demonstrated varying degrees of difference between concussed and non-concussed individuals. The problem with most of these online concussion assessments is that they predominantly rely on consumer grade technology. Typical administration of these reaction time tests involves presenting a visual stimulus on a computer monitor and prompting the test subject to respond as quickly as possible via keypad or computer mouse. However, inherent delays and variabilities are introduced to the reaction time measure by both computer and associated operating systems that the concussion assessment tool is installed on. The authors hypothesized systems that are typically used to collect concussion reaction time data would demonstrate significant errors in reaction time measurements. To remove human bias, a series of experiments was conducted robotically to assess timing errors introduced by reaction time tests under four different conditions. In the first condition, a visual reaction time test was conducted by flashing a visual stimulus on a computer monitor. Detection was via photodiode and mechanical response was delivered via computer mouse. The second condition employed a mobile device for the visual stimulus, and the mechanical response was delivered to the mobile device's touchscreen. The third condition simulated a tactile reaction time test, and mechanical response was delivered via computer mouse. The fourth condition also simulated a tactile reaction time test, but response was delivered to a dedicated device designed to store the interval between stimulus delivery and response, thus bypassing any problems hypothesized to be introduced by computer and/or computer software. There were significant differences in the range of responses recorded from the four different conditions with the reaction time collected from visual stimulus on a mobile device being the worst and the device with dedicated hardware designed for the task being the best. The results suggest that some of the commonly used visual tasks on consumer grade computers could be (and have been) introducing significant errors for reaction time testing and that dedicated hardware designed for the reaction time task is needed to minimize testing errors.

Correction and Validation of Time-Critical Behavioral Measurements over the Internet in the Stage Twin Cohort with More Than 7000 Participants

Behavioral data are increasingly collected over the Internet. This is particularly useful when participants’ own computers can be used as they are, without any modification that relies on their technical skills. However, the temporal accuracy in these settings is generally poor, unknown, and varies substantially across different hard- and software components. This makes it dubious to administer time-critical behavioral tests such as implicit association, reaction time, or various forms of temporal judgment/perception and production. Here, we describe the online collection and subsequent data quality control and adjustment of reaction time and time interval production data from 7127 twins sourced from the Swedish Twin Registry. The purposes are to (1) validate the data that are already and will continue to be reported in forthcoming publications (due to their utility, such as the large sample size and the twin design) and to (2) provide examples of how one might engage in post-hoc analyses of such data, and (3) explore how one might control for systematic influences from specific components in the functional chain. These possible influences include the type and version of the operating system, browser, and multimedia plug-in type

An Accurate Measure of Reaction Time can Provide Objective Metrics of Concussion

There have been numerous reports of neurological assessments of post-concussed athletes and many deploy some type of reaction time assessment. However, most of the assessment tools currently deployed rely on consumer-grade computer systems to collect this data. In a previous report, we demonstrated the inaccuracies that typical computer systems introduce to hardware and software to collect these metrics with robotics (Holden et al, 2020). In that same report, we described the accuracy of a tactile based reaction time test (administered with the Brain Gauge) as approximately 0.3 msec and discussed the shortcoming of other methods for collecting reaction time. The latency errors introduced with those alternative methods were reported as high as 400 msec and the system variabilities could be as high as 80 msec, and these values are several orders of magnitude above the control values previously reported for reaction time (200-220msec) and reaction time variability (10-20 msec). In this report, we examined the reaction time and reaction time variability from 396 concussed individuals and found that there were significant differences in the reaction time metrics obtained from concussed and non-concussed individuals for 14-21 days post-concussion. A survey of the literature did not reveal comparable sensitivity in reaction time testing in concussion studies using alternative methods. This finding was consistent with the prediction put forth by Holden and colleagues with robotics testing of the consumer grade computer systems that are commonly utilized by researchers conducting reaction time testing on concussed individuals. The significant difference in fidelity between the methods commonly used by concussion researchers is attributed to the differences in accuracy of the measures deployed and/or the increases in biological fidelity introduced by tactile based reaction times over visually administered reaction time tests. Additionally, while most of the commonly used computerized testing assessment tools require a pre-season baseline test to predict a neurological insult, the tactile based methods reported in this paper did not utilize any baselines for comparisons. The reaction time data reported was one test of a battery of tests administered to the population studied, and this is the first of a series of papers that will examine each of those tests independently.  

Corticomotor correlates of somatosensory reaction time and variability in individuals with post concussion symptoms

Persistent post concussion symptoms (PPCS) describe the condition when an individual experiences chronic symptoms, particularly fatigue, beyond the expected time of recovery. The aim of this study was to quantify the effect of fatigue and related ongoing symptoms on somatosensory and corticomotor pathways using reaction time (RT) testing, and single-pulse and paired-pulse transcranial magnetic stimulation (TMS). Eighty-three participants (nine female, mean age 37.9 ± 11.5 years) were divided into two groups (persistent symptoms versus asymptomatic) following self-report based upon previously published clinical symptom scores. All participants completed somatosensory and visuomotor RT testing, as well as corticomotor excitability and inhibition measurements via TMS. Participants in the persistent symptom group (n = 38) reported greater number of previous concussions (t = 2.81, p = 0.006) and significantly higher levels of fatigue and related symptoms in the asymptomatic group (n = 45; t = 11.32, p < 0.006). Somatosensory RT showed significant slowing and increased variability in the persistent symptoms group (p < 0.001), however no significant differences were observed between groups for visuomotor RTs. Transcranial magnetic stimulation revealed differences between groups for intracortical inhibition at all stimulus intensities and paired pulse measures. The results indicate that somatosensory and corticomotor systems reflect on-going fatigue. From a practical perspective, objective and simplistic measures such as somatosensory and corticomotor measures can be used in the assessment of PPCS and gauging the efficacy of post concussion rehabilitation programmes.

Reaction Times of Preschool Children on the Ruler Drop Test: A Cross-Sectional Study With Reference Values

Reaction time (RT) tasks assess several brain functions, and a slow RT can be due to various brain diseases, disorders, and acquired conditions. This study examined age and gender differences in RTs of Spanish preschool children on the ruler drop test (RDT) and presents norm-referenced results. Participants were 3,741 children (1,845 girls and 1,896 boys; mean [M] age = 55.93, standard deviation [ SD] = 11.14 months; M body mass index = 15.94, SD = 1.91 kg/m²), selected from 51 schools in southern Spain. We measured RT with the RDT, and we collected both right- and left-hand data. We expressed normative mean RDT values of both hands according to gender and age in percentiles. Based on mean RDT scores, girls exhibited a poorer performance than boys aged 4 years ( p = .032, Cohen's d = - 0.122) and 5 years ( p = .001, Cohen's d = -0.194). For the whole group, RDT performance was faster with increased age, from the age of five years.

Cultural Genomics: Promises and Challenges

In this article, we attempt to integrate recent advances in our understanding of the relations between culture and genes into an emerging field—cultural genomics—and discuss its promises and theoretical and methodological challenges. We first provide a brief review of previous conceptualizations about the relations between culture and genes and then argue that recent advances in molecular evolution research has allowed us to reframe the discussion away from parallel genetic and cultural evolution to focus on the interactions between the two. After outlining the key issues involved in cultural genomics (unit of analysis, timescale, mechanisms, and direction of influence), we provide examples of research for the different levels of interactions between culture and genes. We then discuss ideological, theoretical, and methodological challenges in cultural genomics and propose tentative solutions.

Differentiating Patients at the Memory Clinic With Simple Reaction Time Variables: A Predictive Modeling Approach Using Support Vector Machines and Bayesian Optimization

Background: Mild Cognitive Impairment (MCI) and dementia differ in important ways yet share a future of increased prevalence. Separating these conditions from each other, and from Subjective Cognitive Impairment (SCI), is important for clinical prognoses and treatment, socio-legal interventions, and family adjustments. With costly clinical investigations and an aging population comes a need for more cost-efficient differential diagnostics. Methods: Using supervised machine learning, we investigated nine variables extracted from simple reaction time (SRT) data with respect to their single and conjoined ability to discriminate both MCI/dementia, and SCI/MCI/dementia, compared to-and together with-established psychometric tests. One-hundred-twenty elderly patients (age range = 65-95 years) were recruited when referred to full neuropsychological assessment at a specialized memory clinic in urban Sweden. A freely available SRT task served as index test and was administered and scored objectively by a computer before diagnosis of SCI (n = 17), MCI (n = 53), or dementia (n = 50). As reference standard, diagnosis was decided through the multidisciplinary memory clinic investigation. Bonferroni-Holm corrected P-values for constructed models against the null model are provided. Results: Algorithmic feature selection for the two final multivariable models was performed through recursive feature elimination with 3 × 10-fold cross-validation resampling. For both models, this procedure selected seven predictors of which five were SRT variables. When used as input for a soft-margin, radial-basis support vector machine model tuned via Bayesian optimization, the leave-one-out cross-validated accuracy of the final model for MCI/dementia classification was good (Accuracy = 0.806 [0.716, INS [0].877], P < 0.001) and the final model for SCI/MCI/dementia classification held some merit (Accuracy = 0.650 [0.558, 0.735], P < 0.001). These two models are implemented in a freely available application for research and educatory use. Conclusions: Simple reaction time variables hold some potential in conjunction with established psychometric tests for differentiating MCI/dementia, and SCI/MCI/dementia in these difficult-to-differentiate memory clinic patients. While external validation is needed, their implementation within diagnostic support systems is promising.

Intelligence and Fitness: The Mediating Role of Educational Level

The evolutionary status of intelligence is not clear: It is positively related to various indicators of fitness but negatively to reproductive success as the most important fitness marker. In the present research, we explored the links between intelligence and three fitness indicators: number of children (short-term reproductive success), number of grandchildren (long-term reproductive success), and age at first birth. Participants were individuals in a postreproductive stage ( N = 191; mean age = 66.5 years). Intelligence had a positive correlation with short-term reproductive success and age at first birth but a negative correlation with long-term reproductive success. Participants' education turned out to be a significant mediator of the link between intelligence and criterion measures. The results showed that intelligence can elevate short-term reproductive success. Furthermore, individuals with higher intellectual abilities tended to delay reproduction, which negatively affected their long-term reproductive success. Education was revealed as a very important resource which affects the link between cognitive abilities and fitness, thus proving its evolutionary role in contemporary populations.

Secular Slowing of Auditory Simple Reaction Time in Sweden (1959-1985)

There are indications that simple reaction time might have slowed in Western populations, based on both cohort- and multi-study comparisons. A possible limitation of the latter method in particular is measurement error stemming from methods variance, which results from the fact that instruments and experimental conditions change over time and between studies. We therefore set out to measure the simple auditory reaction time (SRT) of 7,081 individuals (2,997 males and 4,084 females) born in Sweden 1959-1985 (subjects were aged between 27 and 54 years at time of measurement). Depending on age cut-offs and adjustment for aging related slowing of SRT, the data indicate that SRT has increased by between 3 and 16 ms in the 27 birth years covered in the present sample. This slowing is unlikely to be explained by attrition, which was evaluated by comparing the general intelligence × birth-year interactions and standard deviations for both male participants and dropouts, utilizing military conscript cognitive ability data. The present result is consistent with previous studies employing alternative methods, and may indicate the operation of several synergistic factors, such as recent micro-evolutionary trends favoring lower g in Sweden and the effects of industrially produced neurotoxic substances on peripheral nerve conduction velocity.

Future Cognitive Ability: US IQ Prediction until 2060 Based on NAEP

The US National Assessment of Educational Progress (NAEP) measures cognitive competences in reading and mathematics of US students (last 2012 survey N = 50,000). The long-term development based on results from 1971 to 2012 allows a prediction of future cognitive trends. For predicting US averages also demographic trends have to be considered. The largest groups' (White) average of 1978/80 was set at M = 100 and SD = 15 and was used as a benchmark. Based on two past NAEP development periods for 17-year-old students, 1978/80 to 2012 (more optimistic) and 1992 to 2012 (more pessimistic), and demographic projections from the US Census Bureau, cognitive trends until 2060 for the entire age cohort and ethnic groups were estimated. Estimated population averages for 2060 are 103 (optimistic) or 102 (pessimistic). The average rise per decade is dec = 0.76 or 0.45 IQ points. White-Black and White-Hispanic gaps are declining by half, Asian-White gaps treble. The catch-up of minorities (their faster ability growth) contributes around 2 IQ to the general rise of 3 IQ; however, their larger demographic increase reduces the general rise at about the similar amount (-1.4 IQ). Because minorities with faster ability growth also rise in their population proportion the interactive term is positive (around 1 IQ). Consequences for economic and societal development are discussed.

Factors influencing the latency of simple reaction time

Simple reaction time (SRT), the minimal time needed to respond to a stimulus, is a basic measure of processing speed. SRTs were first measured by Francis Galton in the 19th century, who reported visual SRT latencies below 190 ms in young subjects. However, recent large-scale studies have reported substantially increased SRT latencies that differ markedly in different laboratories, in part due to timing delays introduced by the computer hardware and software used for SRT measurement. We developed a calibrated and temporally precise SRT test to analyze the factors that influence SRT latencies in a paradigm where visual stimuli were presented to the left or right hemifield at varying stimulus onset asynchronies (SOAs). Experiment 1 examined a community sample of 1469 subjects ranging in age from 18 to 65. Mean SRT latencies were short (231, 213 ms when corrected for hardware delays) and increased significantly with age (0.55 ms/year), but were unaffected by sex or education. As in previous studies, SRTs were prolonged at shorter SOAs and were slightly faster for stimuli presented in the visual field contralateral to the responding hand. Stimulus detection time (SDT) was estimated by subtracting movement initiation time, measured in a speeded finger tapping test, from SRTs. SDT latencies averaged 131 ms and were unaffected by age. Experiment 2 tested 189 subjects ranging in age from 18 to 82 years in a different laboratory using a larger range of SOAs. Both SRTs and SDTs were slightly prolonged (by 7 ms). SRT latencies increased with age while SDT latencies remained stable. Precise computer-based measurements of SRT latencies show that processing speed is as fast in contemporary populations as in the Victorian era, and that age-related increases in SRT latencies are due primarily to slowed motor output.

Using Score Equating and Measurement Invariance to Examine the Flynn Effect in the Wechsler Adult Intelligence Scale

The Flynn effect (FE; i.e., increase in mean IQ scores over time) is commonly viewed as reflecting population shifts in intelligence, despite the fact that most FE studies have not investigated the assumption of score comparability. Consequently, the extent to which these mean differences in IQ scores reflect population shifts in cognitive abilities versus changes in the instruments used to measure these abilities is unclear. In this study, we used modern psychometric tools to examine the FE. First, we equated raw scores for each common subtest to be on the same scale across instruments. This enabled the combination of scores from all three instruments into one of 13 age groups before converting raw scores into Z scores. Second, using age-based standardized scores for standardization samples, we examined measurement invariance across the second (revised), third, and fourth editions of the Wechsler Adult Intelligence Scale. Results indicate that while scores were equivalent across the third and fourth editions, they were not equivalent across the second and third editions. Results suggest that there is some evidence for an increase in intelligence, but also call into question many published FE findings as presuming the instruments' scores are invariant when this assumption is not warranted.

Neurodevelopmental retardation, as assessed clinically and with magnetoencephalography and electroencephalography, associated with perinatal dioxin exposure

In 1980s Western Europe, human perinatal exposure to background levels of dioxins was rather high. We therefore evaluated the neurodevelopment of our cohort during the prepubertal period and in adolescence. At prepubertal age (7-12 years) 41 children were tested. Both neuromotor functioning and psychological testing were performed (Dutch version of the Wechsler Intelligence Scale for Children (WISC-R) and the Dutch version of the Child Behavior Checklist for ages 4-18 years (CBCL 4-18) and the Teacher Report Form (TRF)). Neurophysiological tests were performed using magnetoencephalography and electroencephalography. In adolescence (14-18 years) the behavior of 33 children was studied again (CBCL and TRF). And the levels of dioxins and dioxin-like PCBs (dl-PCBs) were measured in serum.

RESULTS

At prepubertal age no association was found between perinatal dioxin exposure and verbal, performal and total IQ or with the Touwen's test for neuromotor development. There were behavioral problems associated with both prenatal and postnatal dioxin exposure. In adolescence there were problems associated with the current dioxin levels and dioxin-like-PCBs. Neurophysiological tests revealed clear negative dysfunction. An increase in latency time after a motion stimulus (N2b) of 13 ms (= a delay of 10%) is associated with the higher prenatal dioxin exposure. A similar delay was measured in testing cognitive ability by analyzing the odd ball measurements, N200 and P300, together with an amplitude decrease of 12 %. The delay is indicative of a defective myelinisation and the decrease in amplitude of a loss of neurons.

CONCLUSION

We found effects on behavior in association with the perinatal dioxin exposure and in adolescence in association with the current dioxin levels. Neurophysiological testing is instrumental in the detection of effects of perinatal background levels of chemicals on brain development in normal, healthy children. The clinical, neurological and psychological tests commonly used are not sensitive enough to detect important effects.